Abstract

Since the publication of the American Academy of Pediatrics (AAP) clinical practice guideline for brief resolved unexplained events (BRUEs), a few small, single-center studies have suggested low yield of diagnostic testing in infants presenting with such an event. We conducted this large retrospective multicenter study to determine the role of diagnostic testing in leading to a confirmatory diagnosis in BRUE patients. Secondary analysis from a large multicenter cohort derived from 15 hospitals participating in the BRUE Quality Improvement and Research Collaborative. The study subjects were infants < 1 year of age presenting with a BRUE to the emergency departments (EDs) of these hospitals between October 1, 2015, and September 30, 2018. Potential BRUE cases were identified using a validated algorithm that relies on administrative data. Chart review was conducted to confirm study inclusion/exclusion, AAP risk criteria, final diagnosis, and contribution of test results. Findings were stratified by ED or hospital discharge and AAP risk criteria. For each patient, we identified whether any diagnostic test contributed to the final diagnosis. We distinguished true (contributory) results from false-positive results. Of 2036 patients meeting study criteria, 63.2% were hospitalized, 87.1% qualified as AAP higher risk, and 45.3% received an explanatory diagnosis. Overall, a laboratory test, imaging, or an ancillary test supported the final diagnosis in 3.2% (65/2036, 95% confidence interval [CI] 2.7%-4.4%) of patients. Out of 5163 diagnostic tests overall, 1.1% (33/2897, 95% CI 0.8%-1.5%) laboratory tests and 1.5% (33/2266, 95% CI 1.0%-1.9%) of imaging and ancillary studies contributed to a diagnosis. Although 861 electrocardiograms were performed, no new cardiac diagnoses were identified during the index visit. Diagnostic testing to explain BRUE including for those with AAP higher risk criteria is low yield and rarely contributes to an explanation. Future research is needed to evaluate the role of testing in more specific, at-risk populations.

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